Polyp of Colon
43
7
10
27
Key Insights
Highlights
Success Rate
96% trial completion (above average)
Clinical Risk Assessment
Based on trial outcomes
Moderate Risk
Score: 50/100
2.3%
1 terminated out of 43 trials
96.4%
+9.9% vs benchmark
0%
0 trials in Phase 3/4
11%
3 of 27 completed with results
Key Signals
Data Visualizations
Phase Distribution
Trial Status
Trial Success Rate
Benchmark: 86.5%
Based on 27 completed trials
Clinical Trials (43)
Assessing the Additional Neoplasia Yield of Computer-aided Colonoscopy in Follow-up Patients in a Screening Setting
Reducing Neoplasia Recurrence After Non-thermal Endoscopic Resection of Large Colorectal Polyps
Randomized Trial of Cold EMR Compared to Hybrid Cold EMR.
Combination COMBO Endoscopy Oropharyngeal Airway With High-Flow Nasal Cannula Oxygenation in Sedated Gastrointestinal Endoscopy for Obese Patients
Prevention of Post-Polypectomy Colorectal Bleeding by Clips in Patients on Anticoagulants
Optimizing Timing of Follow-up Colonoscopy
Hybrid-APC Margin Ablation to Prevent Post EMR Adenoma Recurrence
Advanced Endo-therapeutic Procedure : Registry-based Observational Study
Colonic Polypectomy in Cirrhotic Patients With Portal Hypertension
Video/Image Library of Endoscopy Procedures for the Development of AI-empowered Endoscopy Quality Reporting and Educational Modules
Complete Closure After Endoscopic Mucosal Resection of Large Non-Pedunculated Colorectal Polyps
Reducing Neoplasia Recurrence After Endoscopic Resection of Large Colorectal Polyps
Breath Analysis as an Additional Test for Colorectal Cancer Screening to Reduce the Number of Unnecessary Colonoscopies
Real-time Computer-Aided Detection of Colonic Adenomas With NEC WISE VISION® Endoscopy
EAGLE Trial CADDIE Artificial Intelligence Endoscopy
Artificial Intelligence Development for Colorectal Polyp Diagnosis
RITUAL Ultivision AI CADe Randomized Controlled Trial
Combining Artificial Intelligence With Balloon Mucosal Exposure Device for Polyp Detection in Screening Individuals
Impact of Artificial Intelligence (AI) on Adenoma Detection During Colonoscopy in FIT+ Patients.
Deep Learning in Classifying Bowel Obstruction Radiographs